Evolutionary genomics is a key to controlling emerging infectious diseases by identifying virulence genes in the pathogen genome and by revealing patterns and mechanisms of disease spread. Lyme disease, caused by pathogens belonging to the bacterial species complex Borrelia burgdorferi sensu lato, is the most common vector-borne disease in North America and Europe. Although geographically limited, the Lyme disease endemic has greatly expanded in range in recent decades with little predictability. In the past four years, the PI and his collaborators have sequenced the genomes of twenty-three world-wide representative strains of Lyme disease pathogens. Along with the half dozen genomes previously sequenced by this and other research groups, this large amount of Borrelia genomes usher in a new era of understanding the genomic and ecological basis of Lyme disease endemics through evolutionary and comparative genomics. The SC3 support during 1998- 2012 is behind the PI's leading roles in the phylogeny-based selection of strains for whole-genome sequencing, the discovery of widespread recombination and estimation of its rates, and the development of a computational model of B. burgdorferi genome diversity driven by immune escape at a few major surface antigen loci and the outer-surface protein C (ospC) locus in particular. In addition, the SC3 projects resulted in a mature bioinformatics and analytical infrastructure in the PI's lab including, e.g., a customized genome database, a suite of Perl/BioPerl based software tools (DNATweezers), and a simulator of bacterial genome evolution (SimBac). The latter two tools have been released into public repository SourceForge.net as Open Source projects. The PI's specific aims for the proposed SC1 project are to (i) reveal genome variability associated with B. burgdorferi virulence by tests of positive and purifying natural selection, (ii) launch a new line of research in the phylodynamics of Borrelia for predicting the spread of Lyme endemics, and (iii) modernize comparative genomics studies of pathogens by develop evolutionary bioinformatics tools. The PI will develop non-SCORE research proposals through widening collaboration with Borrelia molecular geneticists and Lyme ecologists and developing translational and innovative research programs in population genomics of Lyme disease. To summarize, the overall goal and expected outcomes of the project will be an elucidation of virulence-associated genomic variations, predictive models of the spread of Lyme disease endemics, and a nationally competitive research program in ecology and evolution of emerging infectious diseases. The project helps to control the spread of Lyme disease by identifying virulence genes and by predicting pathogen spread in nature.